Navigating AI in Research
If you're intrigued by the idea of infusing AI into your research journey, read on or contact us. The eResearch team can help you explore the possibilities when your research project meet the power of Artificial Intelligence.
Categories of AI
Generative AI is like a creative powerhouse in the tech world. It's all about teaching computers to make new things – art, music, even stories – by learning from existing examples. It's used in designing unique visuals, crafting new music tracks, and even helping scientists discover new drugs. Generative AI is basically a tool for sparking innovation and creativity across different fields by letting machines generate new stuff on their own.
Machine Learning is like giving brains to computers. It's a part of AI that teaches machines to learn from data and make decisions. This tech powers a lot of cool stuff you see daily – from personalized recommendations on streaming platforms to predicting weather or even detecting fraud in banking. It's all about making computers smarter by learning patterns from data.
Natural Language Processing (NLP) is like teaching computers to understand human language. It's the tech that helps computers read, understand, and even respond to human language just like a person would. Ever used voice assistants like Siri or Alexa? That's NLP in action! It's not just about understanding words; it's also about understanding context and meaning. NLP works behind the scenes in translation apps, chatbots, and even in sorting through tons of text to find specific information. This tech is making it easier for computers to understand us and help us out in a more human-like way.
Computer Vision is like giving eyes to computers. It's all about teaching machines to 'see' and understand the visual world, just like we do. This tech helps computers analyze and make sense of images or videos, which is why it's behind things like facial recognition on your phone or self-driving cars 'seeing' the road. Computer Vision isn't just about recognizing stuff; it's also used in medical imaging, quality control in manufacturing, and even in creating cool Instagram filters! It's making machines see and understand the world around us.
Griffith Research Projects , Ethical AI and Griffith AI Hub
Ethical AI is like a set of rules guiding how AI should behave. It's about making sure that Artificial Intelligence is used in a fair, transparent, and responsible way. Imagine AI that respects privacy, doesn't discriminate, and is transparent about how it works. Ethical AI aims to ensure that technology benefits everyone without causing harm or unfairness. It's like setting boundaries and guidelines to make sure AI helps society without creating problems. This means thinking about things like fairness, accountability, and the impact AI has on people's lives. Ethical AI is all about using tech in a way that's good for everyone.
The Griffith AI Hub (Login Required) is a great resource to learn more about Griffith and AI.
If you'd like more information or are concerned about the ethical use of AI you can contact the teams within Griffith to discuss the topic further regarding your research project.
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